Exploration of programmed cell death-associated characteristics and immune infiltration in neonatal sepsis: new insights from bioinformatics analysis and machine learning.

BACKGROUND: Neonatal sepsis, a perilous medical situation, is typified by the malfunction of organs and serves as the primary reason for neonatal mortality. Nevertheless, the mechanisms underlying newborn sepsis remain ambiguous. Programmed cell death (PCD) has a connection with numerous infectious illnesses and holds a significant function in newborn sepsis, potentially serving as a marker for diagnosing the condition. METHODS: From the GEO public repository, we selected two groups, which we referred to as the training and validation sets, for our analysis of neonatal sepsis. We obtained PCD-related genes from 12 different patterns, including databases and published literature. We first obtained differential expressed genes (DEGs) for neonatal sepsis and controls. Three advanced machine learning techniques, namely LASSO, SVM-RFE, and RF, were employed to identify potential genes connected to PCD. To further validate the results, PPI networks were constructed, artificial neural networks and consensus clustering were used. Subsequently, a neonatal sepsis diagnostic prediction model was developed and evaluated. We conducted an analysis of immune cell infiltration to examine immune cell dysregulation in neonatal sepsis, and we established a ceRNA network based on the identified marker genes. RESULTS: Within the context of neonatal sepsis, a total of 49 genes exhibited an intersection between the differentially expressed genes (DEGs) and those associated with programmed cell death (PCD). Utilizing three distinct machine learning techniques, six genes were identified as common to both DEGs and PCD-associated genes. A diagnostic model was subsequently constructed by integrating differential expression profiles, and subsequently validated by conducting artificial neural networks and consensus clustering. Receiver operating characteristic (ROC) curves were employed to assess the diagnostic merit of the model, which yielded promising results. The immune infiltration analysis revealed notable disparities in patients diagnosed with neonatal sepsis. Furthermore, based on the identified marker genes, the ceRNA network revealed an intricate regulatory interplay. CONCLUSION: In our investigation, we methodically identified six marker genes (AP3B2, STAT3, TSPO, S100A9, GNS, and CX3CR1). An effective diagnostic prediction model emerged from an exhaustive analysis within the training group (AUC 0.930, 95%CI 0.887-0.965) and the validation group (AUC 0.977, 95%CI 0.935-1.000).

Wildland Fires Worsened Population Exposure to PM2.5 Pollution in the Contiguous United States.

As wildland fires become more frequent and intense, fire smoke has significantly worsened the ambient air quality, posing greater health risks. To better understand the impact of wildfire smoke on air quality, we developed a modeling system to estimate daily PM2.5 concentrations attributed to both fire smoke and nonsmoke sources across the contiguous U.S. We found that wildfire smoke has the most significant impact on air quality in the West Coast, followed by the Southeastern U.S. Between 2007 and 2018, fire smoke contributed over 25% of daily PM2.5 concentrations at ∼40% of all regulatory air monitors in the EPA's air quality system (AQS) for more than one month per year. People residing outside the vicinity of an EPA AQS monitor (defined by a 5 km radius) were subject to 36% more smoke impact days compared with those residing nearby. Lowering the national ambient air quality standard (NAAQS) for annual mean PM2.5 concentrations to between 9 and 10 µg/m3 would result in approximately 35-49% of the AQS monitors falling in nonattainment areas, taking into account the impact of fire smoke. If fire smoke contribution is excluded, this percentage would be reduced by 6 and 9%, demonstrating the significant negative impact of wildland fires on air quality.

Wildfire worsens population exposure to PM2.5 pollution in the Continental United States.

As wildfires become more frequent and intense, fire smoke has significantly worsened ambient air quality, posing greater health risks. To better understand the impact of wildfire smoke on air quality, we developed a modeling system to estimate daily PM2.5 concentrations attributed to both fire smoke and non-smoke sources across the Continental U.S. We found that wildfire smoke has the most significant impact on air quality in the West Coast, followed by the Southeastern U.S. Between 2007 and 2018, fire smoke affected daily PM2.5 concentrations at 40% of all regulatory air monitors in EPA's Air Quality System (AQS) for more than one month each year. People residing outside the vicinity of an EPA AQS monitor were subject to 36% more smoke impact days compared to those residing nearby. Lowering the national ambient air quality standard (NAAQS) for annual mean PM2.5 concentrations to between 9 and 10 µg/m3 would result in approximately 29% to 40% of the AQS monitors falling in nonattainment areas without taking into account the contribution from fire smoke. When fire smoke impact is considered, this percentage would rise to 35% to 49%, demonstrating the significant negative impact of wildfires on air quality.

Transcription Factor E2F1 Regulates the Expression of ADRB2.

Adrenergic beta-2-receptor (ADRB2) is highly expressed in various tissue cells, affecting the susceptibility, development, and drug efficacy of diseases such as bronchial asthma and malignant tumor. However, the transcriptional regulatory mechanism of the human ADRB2 gene remains unclear. This study aimed to clarify whether E2F transcription factor 1 (E2F1) was involved in the transcriptional regulation of the human ADRB2 gene. First, the 5' flanking region of the human ADRB2 gene was cloned, and its activity was detected using A549 and BEAS-2B cells. Second, it was found that the overexpression of E2F1 could increase promoter activity by a dual-luciferase reporter gene assay. In contrast, treatment of knockdown of E2F1 significantly resulted in a decrease in its promoter activity. Moreover, mutation of the binding site of E2F1 greatly reduced the potential of human ADRB2 promoter transcriptional activity to be regulated by E2F1 overexpression and knockdown. Additionally, by real-time quantitative PCR and Western blot analysis, we demonstrated that overexpression of E2F1 elevated the ADRB2 mRNA expression and protein levels while si-E2F1 reduced its expression. Finally, the consequence of the chromatin immunoprecipitation assay showed that E2F1 was able to bind to the promoter region of ADRB2 in vivo. These results confirmed that E2F1 upregulated the expression of the human ADRB2 gene.

A satellite-driven model to estimate long-term particulate sulfate levels and attributable mortality burden in China.

Ambient fine particulate matter (PM2.5) pollution is a major environmental and public health challenge in China. In the recent decade, the PM2.5 level has decreased mainly driven by reductions in particulate sulfate as a result of large-scale desulfurization efforts in coal-fired power plants and industrial facilities. Emerging evidence also points to the differential toxicity of particulate sulfate affecting human health. However, estimating the long-term spatiotemporal trend of sulfate is difficult because a ground monitoring network of PM2.5 constituents has not been established in China. Spaceborne sensors such as the Multi-angle Imaging SpectroRadiometer (MISR) instrument can provide complementary information on aerosol size and type. With the help of state-of-the-art machine learning techniques, we developed a sulfate prediction model under support from available ground measurements, MISR-retrieved aerosol microphysical properties, and atmospheric reanalysis data at a spatial resolution of 0.1°. Our sulfate model performed well with an out-of-bag cross-validationR2 of 0.68 at the daily level and 0.93 at the monthly level. We found that the national mean population-weighted sulfate concentration was relatively stable before the Air Pollution Prevention and Control Action Plan was enforced in 2013, ranging from 10.4 to 11.5 µg m-3. But the sulfate level dramatically decreased to 7.7 µg m-3 in 2018, with a change rate of -28.7 % from 2013 to 2018. Correspondingly, the annual mean total non-accidental and cardiopulmonary deaths attributed to sulfate decreased by 40.7 % and 42.3 %, respectively. The long-term, full-coverage sulfate level estimates will support future studies on evaluating air quality policies and understanding the adverse health effect of particulate sulfate.

Optimizing modeling windows to better capture the long-term variation of PM2.5 concentrations in China during 2005-2019.

Including data of different time intervals during model development influences the predicting accuracy of PM2.5 but has not been widely discussed. Therefore, we included modeling data with multiple time windows to identify optimized modeling time windows for capturing the long-term variation of PM2.5 in China during 2005-2019. In general, we incorporated PM2.5 measurements, aerosol optical depth (AOD), meteorological parameters, land use data, and other predictors to train random forest models. The study period was separated into two phases (2013-2019 and 2005-2012) according to the availability of PM2.5 measurements. First, we trained models with two strategies of choosing time windows to compare model performance in predicting PM2.5 from 2013 to 2019, when measurements were available. Strategy 1a (ST1a) refers to training one model with all available data, and Strategy 1b (ST1b) refers to training multiple models each with one-year data. Second, we trained models with additional ten strategies (ST2a-ST2j) based on data from different time windows during 2013-2019 to compare the accuracy in predicting PM2.5 before 2013, when measurements were unavailable. The internal and external cross-validation (CV) indicated that the model performance of ST1b was better than ST1a. Predictions based on ST1a tended to underestimate PM2.5 levels in 2013 and 2014 when PM2.5 concentrations were high, and overestimate after 2017 when PM2.5 dropped dramatically. The external CV of predicting historical PM2.5 was the most robust in ST2i (averaged predictions from two models developed by 2013 and 2014 data, respectively). Models with data closer to historical years and PM2.5 levels performed better in predicting historical PM2.5 concentrations. Our results suggested that training models with data of current-years performed better during 2013-2019, and with data of 2013 and 2014 performed better in predicting historical PM2.5 before 2013 in China. The comparison provided evidence for choosing optimized time windows when predicting long-term PM2.5 concentrations in China.

Application of multi-angle spaceborne observations in characterizing the long-term particulate organic carbon pollution in China.

Ambient PM2.5 pollution is recognized as a leading environmental risk factor, causing significant mortality and morbidity in China. However, the specific contributions of individual PM2.5 constituents remain unclear, primarily due to the lack of a comprehensive ground monitoring network for constituents. This issue is particularly critical for carbonaceous species such as organic carbon (OC) and elemental carbon (EC), which are known for their significant health impacts, and understanding the OC/EC ratio is crucial for identifying pollution sources. To address this, we developed a Super Learner model integrating Multi-angle Imaging SpectroRadiometer (MISR) retrievals to predict daily OC concentrations across China from 2003 to 2019 at a 10-km spatial resolution. Our model demonstrates robust predictive accuracy, as evidenced by a random cross-validation R2 of 0.84 and an RMSE of 4.9 µg/m3, at the daily level. Although MISR is a polar-orbiting instrument, its fractional aerosol data make a significant contribution to the OC exposure model. We then use the model to explore the spatiotemporal distributions of OC and further calculate the EC/OC ratio in China. We compared regional pollution discrepancies and source contributions of carbonaceous pollution over three selected regions: Beijing-Tianjin-Hebei, Fenwei Plain, and Yunnan Province. Our model observes that OC levels are elevated in Northern China due to industrial operations and central heating during the heating season, while in Yunnan, OC pollution is mainly contributed by local forest fires during fire seasons. Additionally, we found that OC pollution in China is likely influenced by climate phenomena such as the El Niño-Southern Oscillation. Considering that climate change is increasing the severity of OC concentrations with more frequent fire events, and its influence on OC formation and dispersion, we suggest emphasizing the role of climate change in future OC pollution control policies. We believe this study will contribute to future epidemiological studies on OC, aiding in refining public health guidelines and enhancing air quality management in China.

Assessment of long-term particulate nitrate air pollution and its health risk in China.

Air pollution is a major environmental and public health challenge in China and the Chinese government has implemented a series of strict air quality policies. However, particulate nitrate (NO3 -) concentration remains high or even increases at monitoring sites despite the total PM2.5 concentration has decreased. Unfortunately, it has been difficult to estimate NO3 - concentration across China due to the lack of a PM2.5 speciation monitoring network. Here, we use a machine learning model incorporating ground measurements and satellite data to characterize the spatiotemporal patterns of NO3 -, thereby understanding the disease burden associated with long-term NO3 - exposure in China. Our results show that existing air pollution control policies are effective, but increased NO3 - of traffic emissions offset reduced NO3 - of industrial emissions. In 2018, the national mean mortality burden attributable to NO3 - was as high as 0.68 million, indicating that targeted regulations are needed to control NO3 - pollution in China.

The relationship between drinking tea and frailty in the community elderly / 中国实用护理杂志

Objective To explore the relationship between drinking tea and frailty among the elderly in the community. Methods A self-designed questionnaire was used to investigate the basic data of the elderly and their status of drinking tea. Tilburg Frailty Index scale was used to evaluate the frailty of the elderly. The physical levels of the elderly were assessed by grip strength, 4 m walking time and time up& go. The factors affecting frailty of the elderly and the relationship between status of drinking tea and frailty were analyzed. Results The incidence of frailty in the community with and without habits of drinking tea was 55.6％(69/124) and 79.3％(96/121).There was significantly difference between them (χ2=15.634, P<0.01). The total scores, body function and mental dimensions of frailty of the former were 4.53± 2.51, 2.46±1.86 and 1.11±0.97 and that of the later were 5.52±2.54, 3.20±1.78 and 1.36±0.97. There was significantly difference between them (t=3.064, 3.178, 2.015, P<0.05) . The grip strength of the former and the latter was (29.06 ± 9.02) kg and (23.96 ± 7.48) kg and there was significantly difference between them (t=-4.824, P<0.01). The Logistic regression analysis showed that the number of complications, the habit of exercise and the habit of drinking tea were the factors influencing frailty. Conclusions Drinking tea may decrease the incidence of frailty and improve fitness level in the elderly. However, investigative research involving larger number of subjects and intervention studies are needed to explore further the relationship between drinking tea and frailty in the future.

The relationship between drinking tea and frailty in the community elderly / 中国实用护理杂志

Objective@#To explore the relationship between drinking tea and frailty among the elderly in the community.@*Methods@#A self-designed questionnaire was used to investigate the basic data of the elderly and their status of drinking tea. Tilburg Frailty Index scale was used to evaluate the frailty of the elderly. The physical levels of the elderly were assessed by grip strength, 4 m walking time and time up & go. The factors affecting frailty of the elderly and the relationship between status of drinking tea and frailty were analyzed.@*Results@#The incidence of frailty in the community with and without habits of drinking tea was 55.6%(69/124) and 79.3%(96/121).There was significantly difference between them (χ2=15.634, P<0.01). The total scores, body function and mental dimensions of frailty of the former were 4.53±2.51, 2.46±1.86 and 1.11±0.97 and that of the later were 5.52±2.54, 3.20±1.78 and 1.36±0.97. There was significantly difference between them (t=3.064, 3.178, 2.015, P<0.05). The grip strength of the former and the latter was (29.06±9.02) kg and (23.96±7.48) kg and there was significantly difference between them (t=-4.824, P<0.01). The Logistic regression analysis showed that the number of complications, the habit of exercise and the habit of drinking tea were the factors influencing frailty.@*Conclusions@#Drinking tea may decrease the incidence of frailty and improve fitness level in the elderly. However, investigative research involving larger number of subjects and intervention studies are needed to explore further the relationship between drinking tea and frailty in the future.

Extraction, Characterization and Antioxidant Activity in vitro of Proteins from Semen Allii Fistulosi.

Semen Allii Fistulosi (PSAF) is the seed of Allium fistulosum L. of the Liliaceae family. The purpose of this study was to extract, characterize, and evaluate the antioxidant activity in vitro of proteins. Using single factor and orthogonal design, the optimum conditions of extraction were determined to be as follows: extraction time 150 min, pH 8.5, temperature 60 °C, and ratio (v/w, mL/g) of extraction solvent to raw material 35. The isoelectric point of the pH was determined to be about 4.4 and 10.2, by measuring the protein content of PSAF solutions at different pH values. The amino acid composition of PSAF was determined by high performance liquid chromatography (HPLC), and the results suggested that the species of amino acids contained in the PSAF was complete. Sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS⁻PAGE) analysis showed the molecular weight was mainly between 40 and 55 kDa, and Fourier-transform infrared spectroscopy (FTIR) characterized prevalent protein absorption peaks. PSAF exhibited potent scavenging activities against DPPH assays, via targeting of hydroxyl and superoxide radicals, while chelating Fe2+ activity and demonstrating weak reducing power. This work revealed that PSAF possessed potential antioxidant activity in vitro, suggesting potential for use of PSAF as a natural antioxidant.

Evaluation of Basal Serum Adrenocorticotropic Hormone and Cortisol Levels and Their Relationship with Nonalcoholic Fatty Liver Disease in Male Patients with Idiopathic Hypogonadotropic Hypogonadism.

BACKGROUND: Prolonged gonadal hormone deficiency in patients with idiopathic hypogonadotropic hypogonadism (IHH) may produce adverse effects on the endocrine homeostasis and metabolism. This study aimed to compare basal serum adrenocorticotropic hormone (ACTH) and cortisol levels between male IHH patients and healthy controls. Moreover, this study compared the basal hypothalamic-pituitary-adrenal (HPA) axis in patients with and without nonalcoholic fatty liver disease (NAFLD), and also evaluated the relationship between basal HPA axis and NAFLD in male IHH patients. METHODS: This was a retrospective case-control study involving 75 Chinese male IHH patients (mean age 21.4 ± 3.8 years, range 17-30 years) and 135 healthy controls after matching for gender and age. All subjects underwent physical examination and blood testing for serum testosterone, luteinizing hormone, follicle-stimulating hormone, ACTH, and cortisol and biochemical tests. RESULTS: Higher basal serum ACTH levels (8.25 ± 3.78 pmol/L vs. 6.97 ± 2.81 pmol/L) and lower cortisol levels (366.70 ± 142.48 nmol/L vs. 452.82 ± 141.53 nmol/L) were observed in male IHH patients than healthy subjects (all p<0.05). IHH patients also showed higher metabolism parameters and higher prevalence rate of NAFLD (34.9% vs. 4.4%) than the controls (all P < 0.05). Basal serum ACTH (9.91 ± 4.98 pmol/L vs. 7.60 ± 2.96 pmol/L) and dehydroepiandrosterone sulfate (2123.7 ± 925.8 µg/L vs. 1417.1 ± 498.4 µg/L) levels were significantly higher in IHH patients with NAFLD than those without NAFLD (all P < 0.05). We also found that basal serum ACTH levels were positively correlated with NAFLD (r = 0.289,p<0.05) and triglyceride levels (r = 0.268, P< 0.05) in male IHH patients. Furthermore, NAFLD was independently associated with ACTH levels in male IHH patients by multiple linear regression analysis. CONCLUSIONS: The male IHH patients showed higher basal serum ACTH levels and lower cortisol levels than matched healthy controls. NAFLD was an independent associated factor for ACTH levels in male IHH patients. These preliminary findings provided evidence of the relationship between basal serum ACTH and NAFLD in male IHH patients.

Evaluation of Basal Serum Adrenocorticotropic Hormone and Cortisol Levels and Their Relationship with Nonalcoholic Fatty Liver Disease in Male Patients with Idiopathic Hypogonadotropic Hypogonadism / 中华医学杂志(英文版)

<p><b>BACKGROUND</b>Prolonged gonadal hormone deficiency in patients with idiopathic hypogonadotropic hypogonadism (IHH) may produce adverse effects on the endocrine homeostasis and metabolism. This study aimed to compare basal serum adrenocorticotropic hormone (ACTH) and cortisol levels between male IHH patients and healthy controls. Moreover, this study compared the basal hypothalamic-pituitary-adrenal (HPA) axis in patients with and without nonalcoholic fatty liver disease (NAFLD), and also evaluated the relationship between basal HPA axis and NAFLD in male IHH patients.</p><p><b>METHODS</b>This was a retrospective case-control study involving 75 Chinese male IHH patients (mean age 21.4 ± 3.8 years, range 17-30 years) and 135 healthy controls after matching for gender and age. All subjects underwent physical examination and blood testing for serum testosterone, luteinizing hormone, follicle-stimulating hormone, ACTH, and cortisol and biochemical tests.</p><p><b>RESULTS</b>Higher basal serum ACTH levels (8.25 ± 3.78 pmol/L vs. 6.97 ± 2.81 pmol/L) and lower cortisol levels (366.70 ± 142.48 nmol/L vs. 452.82 ± 141.53 nmol/L) were observed in male IHH patients than healthy subjects (all p<0.05). IHH patients also showed higher metabolism parameters and higher prevalence rate of NAFLD (34.9% vs. 4.4%) than the controls (all P < 0.05). Basal serum ACTH (9.91 ± 4.98 pmol/L vs. 7.60 ± 2.96 pmol/L) and dehydroepiandrosterone sulfate (2123.7 ± 925.8 μg/L vs. 1417.1 ± 498.4 μg/L) levels were significantly higher in IHH patients with NAFLD than those without NAFLD (all P < 0.05). We also found that basal serum ACTH levels were positively correlated with NAFLD (r = 0.289,p<0.05) and triglyceride levels (r = 0.268, P< 0.05) in male IHH patients. Furthermore, NAFLD was independently associated with ACTH levels in male IHH patients by multiple linear regression analysis.</p><p><b>CONCLUSIONS</b>The male IHH patients showed higher basal serum ACTH levels and lower cortisol levels than matched healthy controls. NAFLD was an independent associated factor for ACTH levels in male IHH patients. These preliminary findings provided evidence of the relationship between basal serum ACTH and NAFLD in male IHH patients.</p>

True lumen stenting for a spontaneously dissected superior mesenteric artery may compromise major intestinal branches and aggravate bowel ischemia.

Optimal endovascular therapy for isolated superior mesenteric artery (SMA) dissection remains undetermined. Here, we report a 56-year-old male with ischemic bowel syndrome caused by such a serious vascular disease. He was treated with endovascular true lumen stenting yet got aggravated in bowel ischemia from unexpected jail of major intestinal branches perfused by the false lumen, requiring subsequent complex rewiring and dilatation procedures to resolve at the cost of excessive fluoroscopic and contrast medium exposure. Thus, when treating patients with isolated SMA dissection with a functioning false lumen, true lumen stenting may inadvertently compromise crucial intestinal branches and should not be indiscriminately considered as the prime therapeutic option.

[Effect of rosiglitazone on ovulation induction in women with polycystic ovary syndrome].

OBJECTIVE: To investigate the effect of rosiglitazone on ovulation induction in women with polycystic ovary syndrome (PCOS). METHODS: Ninety-six PCOS women with insulin resistance (IR) were randomly divided into three groups. Group A (28 cases) received clomiphene citrate (CC) alone. Group B (32 cases) received rosiglitazone alone. And group C (36 cases) received CC and rosiglitazone in combination. All were treated for three menstrual cycles. Homeostasis model assessment insulin resistance (HOMA IR) and ovulation before and after treatment were compared among the 3 groups. RESULTS: After the treatment, HOMA IR in group B and C decreased from 1.2 +/- 0.6 to 0.6 +/- 0.2 and from 1.1 +/- 0.5 to 0.6 +/- 0.4, respectively (P < 0.05). Success rate of ovulation after treatment in group C (80%) was higher than that in group A (59%) and group B (35%, P < 0.05). CONCLUSION: Rosiglitazone therapy improves insulin sensitivity and ovulation induction.

The Immunohistochemical Expression of DNA Topoisomerase II-alpha and E2F-1 in the Breast Carcinoma and Their Relationship with Clinicopathologic Factors

PURPOSE: Clinical courses of breast cancer are very different, and concern for finding a predictable marker of breast carcinomas has increased. This study focused on the relationship between the expressions of DNA topoisomerase II-alpha as a proliferative marker, and E2F-1 as a transcription factor, with clinicopathological factors of infiltrating duct carcinomas of the breast. METHODS: We investigated the expressions of E2F-1 and DNA topoisomerase II-alpha in 43 patients with infiltrating ductal carcinomas using immunohistochemical staining, and the results were analyzed with regard to clinicopathological parameters. RESULTS: Among 43 infiltrating ductal carcinomas, 24 (55.8%) were immunohistochemically negative on E2F-1 and 19 (44.2%) were positive. The expression of E2F-1 correlated with increased tumor size, positive axillary lymph node meta stasis and high stage. The topoisomerase II-alpha index correlated with increased tumor size, positive lymph node metastasis, high stage, high histological grade and negative estrogen receptor. The expression of E2F-1 and the topo II-alpha index were significantly correlated. CONCLUSION: These results suggest that the expressions of DNA topoisomerase II-alpha and E2F-1 play some role as prog nostic factors for infiltrating duct carcinomas of the breast, but much more study will be required.